Bulletin of Chinese Academy of Sciences (Chinese Version)
Keywords
Coastal zones, Satellite-derived bathymetry, Inversion principles, Technological development history
Document Type
Precision Support Technology for Marine Environment
Abstract
Shallow bathymetry data constitute the core foundational information underpinning the ecological, resource, and strategic values of island and coastal zones. Satellite-derived bathymetry has evolved into a key technical means for large-scale acquisition of shallow bathymetry information. Focusing on satellite-based lidar bathymetry, optical imaging bathymetry, and synthetic aperture radar (SAR) bathymetry, this study systematically summarizes the core principles, applicable scenarios, technical strengths, and inherent limitations of each technology. It is shown that satellite-derived bathymetry has undergone an evolutionary shift from theoretical construction to practical application, and from single-method, single-data-source approaches to multi-technology, multi-source data fusion frameworks. In the future, to meet the growing demand for continuous, highly reliable, and refined shallow water bathymetry products in the management of island and coastal zone resources and ecological environment protection, it is imperative to further integrate multi-source satellite-based technologies and develop specialized bathymetric products and service platforms tailored to representative island and coastal applications.
First page
96
Last Page
106
Language
Chinese
Publisher
Bulletin of Chinese Academy of Sciences
References
1. Cohen J E, Small C, Mellinger A, et al. Estimates of coastal populations. Science, 1997, 278: 1209-1213.
2. Weymer B A, Everett M E, Haroon A, et al. The coastal transition zone is an underexplored frontier in hydrology and geoscience. Communications Earth & Environment, 2022, 3(1): 323.
3. Kitchel Z J, Conrad H M, Selden R L, et al. The role of continental shelf bathymetry in shaping marine range shifts in the face of climate change. Global Change Biology, 2022, 28(17): 5185-5199.
4. Barnard P L, Erikson L H, Foxgrover A C, et al. Dynamic flood modeling essential to assess the coastal impacts of climate change. Scientific Reports, 2019, 9(1): 4309.
5. Khanna P, Droxler A W, Nittrouer J A, et al. Coralgal reef morphology records punctuated sea-level rise during the last deglaciation. Nature Communications, 2017, 8(1): 1046.
6. Hauer M E, Hardy D, Kulp S A, et al. Assessing population exposure to coastal flooding due to sea level rise. Nature Communications, 2021, 12(1): 6900.
7. Ferrario F, Beck M W, Storlazzi C D, et al. The effectiveness of coral reefs for coastal hazard risk reduction and adaptation. Nature Communications, 2014, 5(1): 3794.
8. Rocha L A, Pinheiro H T, Shepherd B, et al. Mesophotic coral ecosystems are threatened and ecologically distinct from shallow water reefs. Science, 2018, 361: 281-284.
9. Hu Z, Temmerman S, Zhu Q, et al. Predicting nature-based coastal protection by mangroves under extreme waves. PNAS, 2025, 122(12): e2410883122.
10. Chen B Q, Yang Y M, Xu D W, et al. A dual band algorithm for shallow water depth retrieval from high spatial resolution imagery with no ground truth. ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 151(5): 1-13.
11. Zhou Y, Lu L J, Li L L, et al. A generic method to derive coastal bathymetry from satellite photogrammetry for tsunami hazard assessment. Geophysical Research Letters, 2021, 48(21): e2021GL095142.
12. Xu X, C, Fu D J, Su F Z, et al. Global distribution and decline of mangrove coastal protection extends far beyond area loss. Nature Communications, 2024, 15(1): 10267.
13. Huang Y, Y, Yang H Q, Tang S L, et al. An Appraisal of Atmospheric Correction and Inversion Algorithms for Mapping High-Resolution Bathymetry Over Coral Reef Waters. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 1-11.
14. Liu Y, M, Tang D L, Deng R R, et al. An adaptive blended algorithm approach for deriving bathymetry from multispectral imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 801-817.
15. Parrish C E, Magruder L A, Neuenschwander A L, et al. Validation of ICESat-2 ATLAS bathymetry and analysis of ATLAS’s bathymetric mapping performance. Remote Sensing, 2019, 11(14): 1634-1652.
16. 周国清, 包恺云, 周祥, 等. 水深测量激光雷达系统研究进展. 量子电子学报, 2025, 43: 1-28. Zhou G Q, Bao K Y, Zhou X, et al. Research progress of bathymetric lidar system. Chinese Journal of Quantum Electronics, 2025, 43: 1-28. (in Chinese)
17. Stumpf R P, Holderied K, and Sinclair M. Determination of water depth with high-resolution satellite imagery over variable bottom types. Limnology and Oceanography, 2003, 48(1): 547-556.
18. Mobley C D, The optical properties of water. Handbook of Optics. 2010, 43(3): 43-56.
19. Lyzenga D R, Malinas N P, and Tanis F J. Multispectral bathymetry using a simple physically based algorithm. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(8): 2251-2259.
20. Lee Z P, Carder K L, Mobley C D, et al. Hyperspectral remote sensing for shallow waters: Deriving bottom depths and water properties by optimization. Applied Optics, 1999, 38(18): 3831-43.
21. Mobley C D. Light and Water: Radiative Transfer in Natural Waters. New York: Academic Press, 1994
22. 王小珍. 浅海典型水下地形SAR遥感成像机理和反演研究. 杭州: 浙江大学, 2018. Wang X Z. Research on SAR Remote Sensing Imaging Mechanism and Inversion of Typical Shallow Water Topography. Hangzhou: Zhejiang University, 2018. (in Chinese)
23. Alpers W, Hennings I. A theory of the imaging mechanism of underwater bottom topography by real and synthetic aperture radar. Journal of Geophysical Research: Oceans, 1984, 89(6): 10529-10546.
24. Hersbach H. CMOD5.N: AC-band geophysical model function for equivalent neutral wind. Reading: ECMWF, 2008.
25. Philpot W D. Bathymetric mapping with passive multispectral imagery. Applied Optics, 1989, 28(8): 1569-1578.
26. Dean R. G and Dalrymple R. A. Water wave mechanics for engineers and scientists. Advanced Series on Ocean Engineering. World Scientific, 1991, 2: 368.
27. Cox C S and Munk W H. Measurement of the roughness of the sea surface from photographs of the sun’s glitter. Journal of the Optical Society of America, 1954, 44(11): 838-850.
28. Hennings I, Matthews J, and Metzner M. Sun glitter radiance and radar cross-section modulations of the sea bed. Journal of Geophysical Research, 1994, 99(8): 16303-16326.
29. 曹彬才, 邱振戈, 朱述龙, 等. 高分辨率卫星立体双介质浅水水深测量方法. 测绘学报, 2016, 45(8): 952-963. Cao C B, Qiu Z G, Zhu S L, et al. Shallow water bathymetry through Two-medium photogrammetry using high resolution satellite imagery, Geodaetica et Cartographica Sinica, 2016, 45(8): 952-963. (in Chinese)
30. 王有年, 韩玲, 王云. 水下近景摄影测量试验研究. 测绘学报, 1988, 17(3): 217-224. Wang Y N, Han L, Wang Y. Experimental research of underwater close-range photogrammetry. Acta Geodaetica et Cartographica Sinica, 1988, 17(3): 217-224. (in Chinese)
31. Babbel B J, Parrish C E, and Magruder L A. ICESat-2 elevation retrievals in support of satellite derived bathymetry for global science applications. Geophysical Research Letters, 2021, 48.
32. Parrish C E, Magruder L A, Perry J, et al. Analysis and accuracy assessment of a new global nearshore ICESat-2 bathymetric data product. Earth and Space Science, 2025, 12(8): e2025EA004391.
33. 陈钰宸, 付东洋, 陶邦一, 等. 南海典型岛礁浅海地形遥感监测及时序变化研究. 热带海洋学报, 2025,1-13. Chen Y C, Fu D Y, Tao B Y, et al. Study on remote sensing monitoring and time series change of shallow sea topography of typical islands and reefs in the South China Sea. Journal of Tropical Oceanography, 2025, 1-13. (in Chinese)
34. Polcyn F C, Rollin R A. Remote sensing techniques for the location and measurement of shallow-water features. [2026-01-07]. https://deepblue.lib.umich.edu/items/f9275163-d3f9-43aa-a453-1ce66e2c1ced.
35. Liu Y M, Tang S L, Huang Y Y, et al. Mapping the bathymetry of coral islands with the Landsat series: Quantitative evaluation of the consistency and temporal change detection. International Journal of Applied Earth Observation and Geoinformation, 2025, (5): 142104721.
36. Daly C, Baba W, Bergsma E, et al. The new era of regional coastal bathymetry from space: A showcase for West Africa using optical Sentinel-2 imagery. Remote Sensing of Environment, 2022, (5): 278113084.
37. Almar R, Bergsma E W J, Thoumyre G, et al. Global 1-km coastal bathymetry from Sentinel-2 wave inversion using the Satellite-to-Shores (S2hores) Toolbox. Scientific Data, 2025, 12(1): 1941.
38. Hodúl M, Bird S, Knudby A, et al. Satellite derived photogrammetric bathymetry. ISPRS Journal of Photogrammetry and Remote Sensing, 2018, (3): 142268.
39. 马毅, 张杰, 张靖宇, 等. 浅海水深光学遥感研究进展. 海洋科学进展, 2018, 36(3): 331-351. Ma Y, Zhang J, Zhang J, et al. Progress in shallow water depth mapping from optical remote sensing. Advances in Marine Science, 2018, 36(3): 331-351. (in Chinese)
40. 程亮, 楚森森, 李满春, 等. 卫星遥感浅海水下地形信息提取方法综述. 现代测绘, 2024, 47(6): 1-5. Chen L, Chu S S, Li M C, et al. A review of satellite remote sensing shallow bathymetry extraction methods. Modern Surveying and Mapping, 2024, 47(6): 1-5. (in Chinese)
41. Bian X, Shao Y, Wang S, et al. Shallow water depth retrieval from multitemporal Sentinel-1 SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(9): 2991-3000.
42. 黄龙宇. 基于涌浪特征的SAR浅海地形探测方法研究. 青岛: 自然资源部第一海洋研究所, 2022. Huang L Y. Research on SAR Shallow Sea Topography Detection Method Based on Swell Patterns. Qingdao: The First Institute of Oceanography, Ministry of Natural Resources, 2022. (in Chinese)
43. Wensink G J, Hesselmans G H F M, Calkoen C J, et al. The bathymetry assessment system. Oceanography Series, 1997, (3): 214-223.
Recommended Citation
TANG, Shilin; HUANG, Yuye; LIU, Yongming; YIN, Jianping; CHEN, Deke; HUANG, Ronggang; and LI, Shuang
(2026)
"Satellite-derived bathymetry in island coastal zones: Technology,"
Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 41
:
Iss.
1
, Article 9.
DOI: https://doi.org/10.3724/j.issn.1000-3045.20251219008
Available at:
https://bulletinofcas.researchcommons.org/journal/vol41/iss1/9
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